Overview

Dataset statistics

 Original DataSynthetic Data
Number of variables77
Number of observations2262020162
Missing cells24580
Missing cells (%)1.6%0.0%
Duplicate rows4490
Duplicate rows (%)2.0%0.0%
Total size in memory1.4 MiB551.4 KiB
Average record size in memory64.0 B28.0 B

Variable types

 Original DataSynthetic Data
Numeric77

Alerts

Original DataSynthetic Data
Dataset has 449 (2.0%) duplicate rowsAlert not present in Duplicates
mis_and_disinformation is highly overall correlated with mis_and_disinformation_male and 5 other fieldsmis_and_disinformation is highly overall correlated with mis_and_disinformation_male and 4 other fieldsHigh Correlation
mis_and_disinformation_male is highly overall correlated with mis_and_disinformation and 5 other fieldsmis_and_disinformation_male is highly overall correlated with mis_and_disinformation and 4 other fieldsHigh Correlation
mis_and_disinformation_female is highly overall correlated with mis_and_disinformation and 5 other fieldsmis_and_disinformation_female is highly overall correlated with mis_and_disinformation and 5 other fieldsHigh Correlation
myths is highly overall correlated with mis_and_disinformation and 5 other fieldsmyths is highly overall correlated with mis_and_disinformation and 4 other fieldsHigh Correlation
myths_female is highly overall correlated with mis_and_disinformation and 5 other fieldsmyths_female is highly overall correlated with mis_and_disinformation and 4 other fieldsHigh Correlation
myths_male is highly overall correlated with mis_and_disinformation and 5 other fieldsmyths_male is highly overall correlated with mis_and_disinformation and 4 other fieldsHigh Correlation
new_vaccinations_smoothed is highly overall correlated with mis_and_disinformation and 5 other fieldsnew_vaccinations_smoothed is highly overall correlated with mis_and_disinformation_femaleHigh Correlation
new_vaccinations_smoothed has 2458 (10.9%) missing values Alert not present in Missing
mis_and_disinformation has 3530 (15.6%) zeros Alert not present in Zeros
mis_and_disinformation_male has 6983 (30.9%) zeros Alert not present in Zeros
mis_and_disinformation_female has 8940 (39.5%) zeros Alert not present in Zeros
myths has 6231 (27.5%) zeros Alert not present in Zeros
myths_female has 11337 (50.1%) zeros Alert not present in Zeros
myths_male has 9890 (43.7%) zeros Alert not present in Zeros
new_vaccinations_smoothed has 304 (1.3%) zeros Alert not present in Zeros
Alert not present in mis_and_disinformation_female is highly skewed (γ1 = 33.46757126) Skewed
Alert not present in myths is highly skewed (γ1 = 87.50576782) Skewed
Alert not present in new_vaccinations_smoothed is highly skewed (γ1 = 29.18977356) Skewed

Reproduction

 Original DataSynthetic Data
Analysis started2023-01-21 05:54:14.7157902023-01-21 05:54:24.229833
Analysis finished2023-01-21 05:54:24.2030882023-01-21 05:54:33.758261
Duration9.49 seconds9.53 seconds
Software versionpandas-profiling vv3.6.2pandas-profiling vv3.6.2
Download configurationconfig.jsonconfig.json

Variables

mis_and_disinformation
Real number (ℝ)

 Original DataSynthetic Data
Distinct150320137
Distinct (%)6.6%99.9%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean132.18904194.96919
 Original DataSynthetic Data
Minimum00.25749367
Maximum93428974.4248
Zeros35300
Zeros (%)15.6%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size353.4 KiB78.9 KiB
2023-01-21T05:54:33.931069image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 Original DataSynthetic Data
Minimum00.25749367
5-th percentile00.51735753
Q121.1794579
median84.1513669
Q34834.948195
95-th percentile720.051086.7275
Maximum93428974.4248
Range93428974.1673
Interquartile range (IQR)4633.768738

Descriptive statistics

 Original DataSynthetic Data
Standard deviation463.62593714.19836
Coefficient of variation (CV)3.50729493.6631345
Kurtosis76.7003241.696888
Mean132.18904194.96919
Median Absolute Deviation (MAD)83.5383379
Skewness7.49368435.928329
Sum29901163930968.8
Variance214949.01510079.34
MonotonicityNot monotonicNot monotonic
2023-01-21T05:54:34.196331image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3530
 
15.6%
1 2071
 
9.2%
2 1504
 
6.6%
3 1110
 
4.9%
4 958
 
4.2%
5 716
 
3.2%
6 613
 
2.7%
7 597
 
2.6%
8 453
 
2.0%
9 412
 
1.8%
Other values (1493) 10656
47.1%
ValueCountFrequency (%)
3.027581692 2
 
< 0.1%
1.549239397 2
 
< 0.1%
2.719955444 2
 
< 0.1%
2.921707392 2
 
< 0.1%
1.819850683 2
 
< 0.1%
0.907022059 2
 
< 0.1%
0.4632177353 2
 
< 0.1%
0.5650966167 2
 
< 0.1%
0.7491480708 2
 
< 0.1%
0.6387518644 2
 
< 0.1%
Other values (20127) 20142
99.9%
ValueCountFrequency (%)
0 3530
15.6%
1 2071
9.2%
2 1504
6.6%
3 1110
 
4.9%
4 958
 
4.2%
5 716
 
3.2%
6 613
 
2.7%
7 597
 
2.6%
8 453
 
2.0%
9 412
 
1.8%
ValueCountFrequency (%)
0.2574936748 1
< 0.1%
0.2624304593 1
< 0.1%
0.2693678439 1
< 0.1%
0.2722857893 1
< 0.1%
0.2735600471 1
< 0.1%
0.285967499 1
< 0.1%
0.2899042368 1
< 0.1%
0.2900577188 1
< 0.1%
0.2907913625 1
< 0.1%
0.2923562825 1
< 0.1%
ValueCountFrequency (%)
0.2574936748 1
< 0.1%
0.2624304593 1
< 0.1%
0.2693678439 1
< 0.1%
0.2722857893 1
< 0.1%
0.2735600471 1
< 0.1%
0.285967499 1
< 0.1%
0.2899042368 1
< 0.1%
0.2900577188 1
< 0.1%
0.2907913625 1
< 0.1%
0.2923562825 1
< 0.1%
ValueCountFrequency (%)
0 3530
17.5%
1 2071
10.3%
2 1504
7.5%
3 1110
 
5.5%
4 958
 
4.8%
5 716
 
3.6%
6 613
 
3.0%
7 597
 
3.0%
8 453
 
2.2%
9 412
 
2.0%
 Original DataSynthetic Data
Distinct91220145
Distinct (%)4.0%99.9%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean51.71047745.556214
 Original DataSynthetic Data
Minimum00.0017139363
Maximum33513319.9016
Zeros69830
Zeros (%)30.9%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size353.4 KiB78.9 KiB
2023-01-21T05:54:34.446217image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 Original DataSynthetic Data
Minimum00.0017139363
5-th percentile00.0040189742
Q100.012929554
median30.075563148
Q3171.4213123
95-th percentile294169.28096
Maximum33513319.9016
Range33513319.8999
Interquartile range (IQR)171.4083827

Descriptive statistics

 Original DataSynthetic Data
Standard deviation179.22929233.83656
Coefficient of variation (CV)3.4660155.1329235
Kurtosis67.37679772.5485
Mean51.71047745.556214
Median Absolute Deviation (MAD)30.070963144
Skewness7.02320947.911963
Sum1169691918504.39
Variance32123.13854679.535
MonotonicityNot monotonicNot monotonic
2023-01-21T05:54:34.708870image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6983
30.9%
1 2532
 
11.2%
2 1608
 
7.1%
3 1156
 
5.1%
4 886
 
3.9%
5 687
 
3.0%
6 562
 
2.5%
7 443
 
2.0%
8 344
 
1.5%
10 313
 
1.4%
Other values (902) 7106
31.4%
ValueCountFrequency (%)
0.007497055456 2
 
< 0.1%
0.01658315025 2
 
< 0.1%
142.8185272 2
 
< 0.1%
0.009448382072 2
 
< 0.1%
0.2914951742 2
 
< 0.1%
0.0579393208 2
 
< 0.1%
0.01699636504 2
 
< 0.1%
0.06248620898 2
 
< 0.1%
0.1034393981 2
 
< 0.1%
1.121963143 2
 
< 0.1%
Other values (20135) 20142
99.9%
ValueCountFrequency (%)
0 6983
30.9%
1 2532
 
11.2%
2 1608
 
7.1%
3 1156
 
5.1%
4 886
 
3.9%
5 687
 
3.0%
6 562
 
2.5%
7 443
 
2.0%
8 344
 
1.5%
9 300
 
1.3%
ValueCountFrequency (%)
0.001713936334 1
< 0.1%
0.001778369537 1
< 0.1%
0.001795734162 1
< 0.1%
0.001853806083 1
< 0.1%
0.001881818054 1
< 0.1%
0.001883565099 1
< 0.1%
0.001904274337 1
< 0.1%
0.001975537278 1
< 0.1%
0.001990786754 1
< 0.1%
0.0020405096 1
< 0.1%
ValueCountFrequency (%)
0.001713936334 1
< 0.1%
0.001778369537 1
< 0.1%
0.001795734162 1
< 0.1%
0.001853806083 1
< 0.1%
0.001881818054 1
< 0.1%
0.001883565099 1
< 0.1%
0.001904274337 1
< 0.1%
0.001975537278 1
< 0.1%
0.001990786754 1
< 0.1%
0.0020405096 1
< 0.1%
ValueCountFrequency (%)
0 6983
34.6%
1 2532
 
12.6%
2 1608
 
8.0%
3 1156
 
5.7%
4 886
 
4.4%
5 687
 
3.4%
6 562
 
2.8%
7 443
 
2.2%
8 344
 
1.7%
9 300
 
1.5%
 Original DataSynthetic Data
Distinct71720141
Distinct (%)3.2%99.9%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean32.9719270.63210664
 Original DataSynthetic Data
Minimum04.8112943 × 10-6
Maximum2745375.33386
Zeros89400
Zeros (%)39.5%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size353.4 KiB78.9 KiB
2023-01-21T05:54:34.965553image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 Original DataSynthetic Data
Minimum04.8112943 × 10-6
5-th percentile03.4263846 × 10-5
Q100.00016232475
median10.0010686517
Q380.018942724
95-th percentile1711.6793667
Maximum2745375.33386
Range2745375.33386
Interquartile range (IQR)80.018780399

Descriptive statistics

 Original DataSynthetic Data
Standard deviation127.972816.1599326
Coefficient of variation (CV)3.88126579.7450845
Kurtosis86.1629251547.1344
Mean32.9719270.63210664
Median Absolute Deviation (MAD)10.001024836
Skewness7.97983733.467571
Sum74582512744.534
Variance16377.04137.944767
MonotonicityNot monotonicNot monotonic
2023-01-21T05:54:35.223666image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8940
39.5%
1 2841
 
12.6%
2 1752
 
7.7%
3 1078
 
4.8%
4 738
 
3.3%
5 556
 
2.5%
6 446
 
2.0%
7 369
 
1.6%
8 291
 
1.3%
9 244
 
1.1%
Other values (707) 5365
23.7%
ValueCountFrequency (%)
7.466223178 × 10-52
 
< 0.1%
0.008932402357 2
 
< 0.1%
4.873222497 × 10-52
 
< 0.1%
0.0001398147579 2
 
< 0.1%
0.0003148161049 2
 
< 0.1%
0.001261505648 2
 
< 0.1%
0.7851961255 2
 
< 0.1%
0.0003220156941 2
 
< 0.1%
0.0003940643219 2
 
< 0.1%
0.0001623247517 2
 
< 0.1%
Other values (20131) 20142
99.9%
ValueCountFrequency (%)
0 8940
39.5%
1 2841
 
12.6%
2 1752
 
7.7%
3 1078
 
4.8%
4 738
 
3.3%
5 556
 
2.5%
6 446
 
2.0%
7 369
 
1.6%
8 291
 
1.3%
9 244
 
1.1%
ValueCountFrequency (%)
4.811294275 × 10-61
< 0.1%
5.135927495 × 10-61
< 0.1%
5.690041235 × 10-61
< 0.1%
5.765156857 × 10-61
< 0.1%
5.809421054 × 10-61
< 0.1%
5.9827521 × 10-61
< 0.1%
6.099553048 × 10-61
< 0.1%
6.262137958 × 10-61
< 0.1%
6.278678484 × 10-61
< 0.1%
6.307185231 × 10-61
< 0.1%
ValueCountFrequency (%)
4.811294275 × 10-61
< 0.1%
5.135927495 × 10-61
< 0.1%
5.690041235 × 10-61
< 0.1%
5.765156857 × 10-61
< 0.1%
5.809421054 × 10-61
< 0.1%
5.9827521 × 10-61
< 0.1%
6.099553048 × 10-61
< 0.1%
6.262137958 × 10-61
< 0.1%
6.278678484 × 10-61
< 0.1%
6.307185231 × 10-61
< 0.1%
ValueCountFrequency (%)
0 8940
44.3%
1 2841
 
14.1%
2 1752
 
8.7%
3 1078
 
5.3%
4 738
 
3.7%
5 556
 
2.8%
6 446
 
2.2%
7 369
 
1.8%
8 291
 
1.4%
9 244
 
1.2%

myths
Real number (ℝ)

 Original DataSynthetic Data
Distinct84920093
Distinct (%)3.8%99.7%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean47.7376225.1294338 × 10-7
 Original DataSynthetic Data
Minimum05.5744087 × 10-13
Maximum42040.0021937087
Zeros62310
Zeros (%)27.5%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size353.4 KiB78.9 KiB
2023-01-21T05:54:35.521942image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 Original DataSynthetic Data
Minimum05.5744087 × 10-13
5-th percentile04.1772176 × 10-12
Q102.084769 × 10-11
median41.5116586 × 10-10
Q3242.2952317 × 10-9
95-th percentile2281.928308 × 10-7
Maximum42040.0021937087
Range42040.0021937087
Interquartile range (IQR)242.274384 × 10-9

Descriptive statistics

 Original DataSynthetic Data
Standard deviation157.697011.9959067 × 10-5
Coefficient of variation (CV)3.303411538.910857
Kurtosis84.4816848622.3672
Mean47.7376225.1294338 × 10-7
Median Absolute Deviation (MAD)41.4584707 × 10-10
Skewness7.414039287.505768
Sum10798250.010341964
Variance24868.3473.9836431 × 10-10
MonotonicityNot monotonicNot monotonic
2023-01-21T05:54:35.777810image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6231
27.5%
1 2581
 
11.4%
2 1495
 
6.6%
3 997
 
4.4%
4 788
 
3.5%
5 636
 
2.8%
6 556
 
2.5%
7 442
 
2.0%
8 387
 
1.7%
9 340
 
1.5%
Other values (839) 8167
36.1%
ValueCountFrequency (%)
1.600090373 × 10-112
 
< 0.1%
2.036454165 × 10-112
 
< 0.1%
2.708205535 × 10-112
 
< 0.1%
1.148236627 × 10-112
 
< 0.1%
1.148199938 × 10-102
 
< 0.1%
3.621257461 × 10-112
 
< 0.1%
4.528115383 × 10-102
 
< 0.1%
3.017615021 × 10-122
 
< 0.1%
3.179078528 × 10-112
 
< 0.1%
1.607396882 × 10-92
 
< 0.1%
Other values (20083) 20142
99.9%
ValueCountFrequency (%)
0 6231
27.5%
1 2581
11.4%
2 1495
 
6.6%
3 997
 
4.4%
4 788
 
3.5%
5 636
 
2.8%
6 556
 
2.5%
7 442
 
2.0%
8 387
 
1.7%
9 340
 
1.5%
ValueCountFrequency (%)
5.574408665 × 10-131
< 0.1%
7.25037543 × 10-131
< 0.1%
7.888903289 × 10-131
< 0.1%
8.03220229 × 10-131
< 0.1%
8.076476228 × 10-131
< 0.1%
8.601234959 × 10-131
< 0.1%
8.87349005 × 10-131
< 0.1%
8.896876291 × 10-131
< 0.1%
9.042051504 × 10-131
< 0.1%
9.164562555 × 10-131
< 0.1%
ValueCountFrequency (%)
5.574408665 × 10-131
< 0.1%
7.25037543 × 10-131
< 0.1%
7.888903289 × 10-131
< 0.1%
8.03220229 × 10-131
< 0.1%
8.076476228 × 10-131
< 0.1%
8.601234959 × 10-131
< 0.1%
8.87349005 × 10-131
< 0.1%
8.896876291 × 10-131
< 0.1%
9.042051504 × 10-131
< 0.1%
9.164562555 × 10-131
< 0.1%
ValueCountFrequency (%)
0 6231
30.9%
1 2581
12.8%
2 1495
 
7.4%
3 997
 
4.9%
4 788
 
3.9%
5 636
 
3.2%
6 556
 
2.8%
7 442
 
2.2%
8 387
 
1.9%
9 340
 
1.7%

myths_female
Real number (ℝ)

 Original DataSynthetic Data
Distinct36720128
Distinct (%)1.6%99.8%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean11.8463750.88741908
 Original DataSynthetic Data
Minimum00.0009409269
Maximum1521146.70242
Zeros113370
Zeros (%)50.1%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size353.4 KiB78.9 KiB
2023-01-21T05:54:36.031368image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 Original DataSynthetic Data
Minimum00.0009409269
5-th percentile00.0020053099
Q100.004977763
median00.017849388
Q340.12708842
95-th percentile523.6867018
Maximum1521146.70242
Range1521146.70148
Interquartile range (IQR)40.12211066

Descriptive statistics

 Original DataSynthetic Data
Standard deviation44.952954.4033723
Coefficient of variation (CV)3.79465874.9619987
Kurtosis151.20784219.98198
Mean11.8463750.88741908
Median Absolute Deviation (MAD)00.015353912
Skewness9.371839111.610792
Sum26796517892.143
Variance2020.767719.389688
MonotonicityNot monotonicNot monotonic
2023-01-21T05:54:36.584314image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 11337
50.1%
1 2712
 
12.0%
2 1432
 
6.3%
3 921
 
4.1%
4 667
 
2.9%
5 438
 
1.9%
6 392
 
1.7%
7 322
 
1.4%
9 257
 
1.1%
8 214
 
0.9%
Other values (357) 3928
 
17.4%
ValueCountFrequency (%)
0.1657812148 2
 
< 0.1%
0.01287199184 2
 
< 0.1%
0.01083931886 2
 
< 0.1%
1.200712085 2
 
< 0.1%
0.01262701303 2
 
< 0.1%
0.003183210036 2
 
< 0.1%
0.002357335528 2
 
< 0.1%
0.0109860776 2
 
< 0.1%
0.01557181682 2
 
< 0.1%
0.06065730378 2
 
< 0.1%
Other values (20118) 20142
99.9%
ValueCountFrequency (%)
0 11337
50.1%
1 2712
 
12.0%
2 1432
 
6.3%
3 921
 
4.1%
4 667
 
2.9%
5 438
 
1.9%
6 392
 
1.7%
7 322
 
1.4%
8 214
 
0.9%
9 257
 
1.1%
ValueCountFrequency (%)
0.0009409268969 1
< 0.1%
0.0009473963291 1
< 0.1%
0.001031626598 1
< 0.1%
0.001043590135 1
< 0.1%
0.001104090828 1
< 0.1%
0.001116379164 1
< 0.1%
0.001116638887 1
< 0.1%
0.001135243801 1
< 0.1%
0.001139126485 1
< 0.1%
0.001139322994 1
< 0.1%
ValueCountFrequency (%)
0.0009409268969 1
< 0.1%
0.0009473963291 1
< 0.1%
0.001031626598 1
< 0.1%
0.001043590135 1
< 0.1%
0.001104090828 1
< 0.1%
0.001116379164 1
< 0.1%
0.001116638887 1
< 0.1%
0.001135243801 1
< 0.1%
0.001139126485 1
< 0.1%
0.001139322994 1
< 0.1%
ValueCountFrequency (%)
0 11337
56.2%
1 2712
 
13.5%
2 1432
 
7.1%
3 921
 
4.6%
4 667
 
3.3%
5 438
 
2.2%
6 392
 
1.9%
7 322
 
1.6%
8 214
 
1.1%
9 257
 
1.3%

myths_male
Real number (ℝ)

 Original DataSynthetic Data
Distinct45620127
Distinct (%)2.0%99.8%
Missing00
Missing (%)0.0%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean17.3681262.4123741
 Original DataSynthetic Data
Minimum00.0014087727
Maximum1365523.39032
Zeros98900
Zeros (%)43.7%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size353.4 KiB78.9 KiB
2023-01-21T05:54:36.865528image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 Original DataSynthetic Data
Minimum00.0014087727
5-th percentile00.0027560253
Q100.0061015229
median10.022812185
Q370.23624865
95-th percentile8810.077938
Maximum1365523.39032
Range1365523.38891
Interquartile range (IQR)70.23014713

Descriptive statistics

 Original DataSynthetic Data
Standard deviation58.29102212.685512
Coefficient of variation (CV)3.35620685.2585176
Kurtosis64.714635355.3302
Mean17.3681262.4123741
Median Absolute Deviation (MAD)10.019612003
Skewness6.726311313.915636
Sum39286748638.286
Variance3397.8432160.9222
MonotonicityNot monotonicNot monotonic
2023-01-21T05:54:37.128420image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9890
43.7%
1 2596
 
11.5%
2 1506
 
6.7%
3 1018
 
4.5%
4 746
 
3.3%
5 639
 
2.8%
6 435
 
1.9%
7 402
 
1.8%
8 308
 
1.4%
9 307
 
1.4%
Other values (446) 4773
21.1%
ValueCountFrequency (%)
0.113289766 2
 
< 0.1%
0.03909193352 2
 
< 0.1%
0.002846202813 2
 
< 0.1%
0.01819017529 2
 
< 0.1%
0.1021878049 2
 
< 0.1%
0.02539433353 2
 
< 0.1%
0.007072576787 2
 
< 0.1%
0.003821014892 2
 
< 0.1%
0.07215686142 2
 
< 0.1%
0.03538630158 2
 
< 0.1%
Other values (20117) 20142
99.9%
ValueCountFrequency (%)
0 9890
43.7%
1 2596
 
11.5%
2 1506
 
6.7%
3 1018
 
4.5%
4 746
 
3.3%
5 639
 
2.8%
6 435
 
1.9%
7 402
 
1.8%
8 308
 
1.4%
9 307
 
1.4%
ValueCountFrequency (%)
0.001408772659 1
< 0.1%
0.001488958253 1
< 0.1%
0.001499351813 1
< 0.1%
0.001503663138 1
< 0.1%
0.001528530149 1
< 0.1%
0.001529715722 1
< 0.1%
0.001552285627 1
< 0.1%
0.00155452115 1
< 0.1%
0.001575703733 1
< 0.1%
0.001578219817 1
< 0.1%
ValueCountFrequency (%)
0.001408772659 1
< 0.1%
0.001488958253 1
< 0.1%
0.001499351813 1
< 0.1%
0.001503663138 1
< 0.1%
0.001528530149 1
< 0.1%
0.001529715722 1
< 0.1%
0.001552285627 1
< 0.1%
0.00155452115 1
< 0.1%
0.001575703733 1
< 0.1%
0.001578219817 1
< 0.1%
ValueCountFrequency (%)
0 9890
49.1%
1 2596
 
12.9%
2 1506
 
7.5%
3 1018
 
5.0%
4 746
 
3.7%
5 639
 
3.2%
6 435
 
2.2%
7 402
 
2.0%
8 308
 
1.5%
9 307
 
1.5%

new_vaccinations_smoothed
Real number (ℝ)

 Original DataSynthetic Data
Distinct1597820137
Distinct (%)79.2%99.9%
Missing24580
Missing (%)10.9%0.0%
Infinite00
Infinite (%)0.0%0.0%
Mean273046.672668.5122
 Original DataSynthetic Data
Minimum01.3695122
Maximum100379951247604.2
Zeros3040
Zeros (%)1.3%0.0%
Negative00
Negative (%)0.0%0.0%
Memory size353.4 KiB78.9 KiB
2023-01-21T05:54:37.399408image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

 Original DataSynthetic Data
Minimum01.3695122
5-th percentile39612.471789
Q16362100.70676
median41651234.97049
Q3217664.75690.17796
95-th percentile12668596742.1515
Maximum100379951247604.2
Range100379951247602.9
Interquartile range (IQR)211302.75589.4712

Descriptive statistics

 Original DataSynthetic Data
Standard deviation778429.3323702.07
Coefficient of variation (CV)2.85090218.8821293
Kurtosis51.5532961142.5132
Mean273046.672668.5122
Median Absolute Deviation (MAD)40250179.19913
Skewness6.495010529.189774
Sum5.505167 × 10953802543
Variance6.0595222 × 10115.617881 × 108
MonotonicityNot monotonicNot monotonic
2023-01-21T05:54:37.663621image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 304
 
1.3%
1926 71
 
0.3%
6049 61
 
0.3%
37853 57
 
0.3%
4431 52
 
0.2%
2915 51
 
0.2%
34002 50
 
0.2%
201797 50
 
0.2%
1401 45
 
0.2%
23552 43
 
0.2%
Other values (15968) 19378
85.7%
(Missing) 2458
 
10.9%
ValueCountFrequency (%)
210.4053955 2
 
< 0.1%
797.4474487 2
 
< 0.1%
91.17314148 2
 
< 0.1%
125.5846176 2
 
< 0.1%
644.6708984 2
 
< 0.1%
681.6853027 2
 
< 0.1%
264.7999878 2
 
< 0.1%
716.2763672 2
 
< 0.1%
193.1675568 2
 
< 0.1%
343.0980835 2
 
< 0.1%
Other values (20127) 20142
99.9%
ValueCountFrequency (%)
0 304
1.3%
2 1
 
< 0.1%
18 1
 
< 0.1%
19 1
 
< 0.1%
26 2
 
< 0.1%
28 2
 
< 0.1%
33 2
 
< 0.1%
34 2
 
< 0.1%
35 2
 
< 0.1%
36 3
 
< 0.1%
ValueCountFrequency (%)
1.3695122 1
< 0.1%
1.500377178 1
< 0.1%
1.564958572 1
< 0.1%
1.569641471 1
< 0.1%
1.609022021 1
< 0.1%
1.63750267 1
< 0.1%
1.647035837 1
< 0.1%
1.679669738 1
< 0.1%
1.689743638 1
< 0.1%
1.756750226 1
< 0.1%
ValueCountFrequency (%)
1.3695122 1
< 0.1%
1.500377178 1
< 0.1%
1.564958572 1
< 0.1%
1.569641471 1
< 0.1%
1.609022021 1
< 0.1%
1.63750267 1
< 0.1%
1.647035837 1
< 0.1%
1.679669738 1
< 0.1%
1.689743638 1
< 0.1%
1.756750226 1
< 0.1%
ValueCountFrequency (%)
0 304
1.5%
2 1
 
< 0.1%
18 1
 
< 0.1%
19 1
 
< 0.1%
26 2
 
< 0.1%
28 2
 
< 0.1%
33 2
 
< 0.1%
34 2
 
< 0.1%
35 2
 
< 0.1%
36 3
 
< 0.1%

Interactions

Original Data

2023-01-21T05:54:22.095987image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:32.126392image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:14.981929image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:24.910980image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:16.126086image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:26.057014image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:17.336587image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:27.232481image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:18.542446image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:28.426829image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:19.699427image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:29.568683image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:20.904965image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:30.963684image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:22.254586image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:32.283230image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:15.134059image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:25.064362image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:16.292432image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:26.215366image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:17.508359image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:27.393201image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:18.694551image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:28.578577image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:19.870666image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:29.738358image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:21.064134image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:31.128482image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:22.430328image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:32.462859image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:15.300277image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:25.228103image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:16.465044image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:26.379182image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:17.690079image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:27.568928image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:18.879042image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:28.745640image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:20.046559image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:29.907055image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:21.248374image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:31.289130image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:22.595368image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:32.653477image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:15.455469image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:25.396795image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:16.634201image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:26.548334image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:17.866967image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:27.738542image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:19.035838image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:28.918895image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:20.213237image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:30.290641image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:21.411758image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:31.464103image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:22.753047image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:32.825679image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:15.611895image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:25.549083image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:16.801750image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:26.710927image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:18.024211image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:27.901951image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:19.204539image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:29.077960image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:20.370167image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:30.454061image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:21.571680image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:31.621866image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:23.402495image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:33.000837image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:15.790406image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:25.714930image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:16.987616image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:26.884871image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:18.199844image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:28.085396image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:19.369466image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:29.240811image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:20.547700image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:30.629381image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:21.746103image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:31.788958image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:23.580380image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:33.176657image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:15.954501image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:25.880484image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:17.163592image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:27.062089image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:18.376527image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:28.252461image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:19.536747image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:29.403274image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:20.727616image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:30.793954image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

2023-01-21T05:54:21.925926image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:31.945641image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Correlations

Original Data

2023-01-21T05:54:37.837615image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Synthetic Data

2023-01-21T05:54:38.035772image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Original Data

mis_and_disinformationmis_and_disinformation_malemis_and_disinformation_femalemythsmyths_femalemyths_malenew_vaccinations_smoothed
mis_and_disinformation1.0000.9440.9110.8890.8240.8580.571
mis_and_disinformation_male0.9441.0000.8690.8660.8120.8580.544
mis_and_disinformation_female0.9110.8691.0000.8450.8140.8340.530
myths0.8890.8660.8451.0000.8860.9230.602
myths_female0.8240.8120.8140.8861.0000.8340.549
myths_male0.8580.8580.8340.9230.8341.0000.563
new_vaccinations_smoothed0.5710.5440.5300.6020.5490.5631.000

Synthetic Data

mis_and_disinformationmis_and_disinformation_malemis_and_disinformation_femalemythsmyths_femalemyths_malenew_vaccinations_smoothed
mis_and_disinformation1.0000.9920.9570.8070.9610.973-0.468
mis_and_disinformation_male0.9921.0000.9440.8280.9740.986-0.449
mis_and_disinformation_female0.9570.9441.0000.7030.9310.907-0.502
myths0.8070.8280.7031.0000.8570.862-0.021
myths_female0.9610.9740.9310.8571.0000.984-0.371
myths_male0.9730.9860.9070.8620.9841.000-0.406
new_vaccinations_smoothed-0.468-0.449-0.502-0.021-0.371-0.4061.000

Missing values

Original Data

2023-01-21T05:54:23.811093image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
A simple visualization of nullity by column.

Synthetic Data

2023-01-21T05:54:33.411497image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
A simple visualization of nullity by column.

Original Data

2023-01-21T05:54:24.072039image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Synthetic Data

2023-01-21T05:54:33.635926image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Original Data

mis_and_disinformationmis_and_disinformation_malemis_and_disinformation_femalemythsmyths_femalemyths_malenew_vaccinations_smoothed
0000101NaN
1100101NaN
2200000NaN
3200000NaN
4000100NaN
5100100NaN
6101000NaN
7000000NaN
8110000NaN
9000000NaN

Synthetic Data

mis_and_disinformationmis_and_disinformation_malemis_and_disinformation_femalemythsmyths_femalemyths_malenew_vaccinations_smoothed
00.8819260.0072940.0000961.441762e-110.0025020.003399433.755737
10.5616490.0043370.0000464.396738e-120.0019040.002689206.921494
20.7990670.0064210.0000495.791453e-120.0023900.003687171.967133
327.9812410.8313500.0567609.115203e-110.1237050.081263270.183807
43417.765625828.43133524.0438042.883288e-0711.47537339.91558823.367708
51.2873630.0153600.0000774.580738e-110.0034870.004829806.266113
62.2755460.0312790.0003251.437807e-110.0100650.014703222.214279
70.4760460.0039180.0000206.979158e-110.0050620.0063681806.305420
82.3848560.0277740.0012966.562452e-120.0094620.008861231.261658
90.4069590.0028020.0000101.710320e-100.0037300.0044563761.653076

Original Data

mis_and_disinformationmis_and_disinformation_malemis_and_disinformation_femalemythsmyths_femalemyths_malenew_vaccinations_smoothed
22610200000NaN
22611100101NaN
22612000000NaN
2261332198101NaN
2261439155926NaN
22615614010714NaN
2261642207921NaN
22617402531628NaN
2261843226502NaN
226195528141115NaN

Synthetic Data

mis_and_disinformationmis_and_disinformation_malemis_and_disinformation_femalemythsmyths_femalemyths_malenew_vaccinations_smoothed
20152111.2976006.0632410.1018192.119309e-090.2392960.67024729.048500
201538.5419160.1781450.0014356.160439e-100.0402900.054823410.363800
201540.5288510.0061460.0000171.129179e-100.0035150.0051038263.362305
201550.9605150.0123570.0000363.918914e-100.0043790.0056645405.026367
201561.0105560.0102430.0000614.024147e-110.0038560.005503400.746857
201570.7820990.0089830.0001585.700643e-120.0040490.004647341.378448
201581.0917760.0139790.0001356.930960e-120.0051390.007120221.266937
201590.5324890.0062240.0006011.007859e-100.0175820.0040547451.645996
20160340.91253735.1492460.4027806.029190e-091.3611102.38124410.289628
201615.3108010.0510270.0013974.791975e-100.0137090.0161003292.263916

Duplicate rows

Original Data

mis_and_disinformationmis_and_disinformation_malemis_and_disinformation_femalemythsmyths_femalemyths_malenew_vaccinations_smoothed# duplicates
178000000NaN391
259100000NaN121
00000000.095
194000100NaN72
302110000NaN58
333200000NaN57
358210000NaN36
283101000NaN30
266100100NaN27
202000101NaN21

Synthetic Data

mis_and_disinformationmis_and_disinformation_malemis_and_disinformation_femalemythsmyths_femalemyths_malenew_vaccinations_smoothed# duplicates
Dataset does not contain duplicate rows.